• Ocean Science Journal
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• v.40 no.4
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• pp.213-220
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• 2005

In this paper, image processing technique that reduces video images of buoy motion to yield time series of image coordinates of buoy objects will be investigated. The buoy motion images are noisy due to time-varying brightness as well as non-uniform background illumination. The occurrence of boats, wakes, and wind-induced white caps interferes significantly in recognition of buoy objects. Thus, semi-automated procedures consisting of object recognition and image measurement aspects will be conducted. These offer more satisfactory results than a manual process. Spectral analysis shows that the image coordinates of buoy objects represent wave motion well, indicating its usefulness in the analysis of wave characteristics.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.109-116
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• 2011

In this paper, we introduce non-touch style interface system technology without any touch style controlling mechanism, which is called as "Air-interface". To develop this system, we used the full reflection principle of infrared (IR) light and then user's hand is separated from the background with the obtained image at every frame. The segmented hand region at every frame is used as input data for an hand-motion recognition module, and the hand-motion recognition module performs a suitable control event that has been mapped into the specified hand-motion through verifying the hand-motion. In this paper, we introduce some developed and suggested methods for image processing and hand-motion recognition. The developed air-touch technology will be very useful for advertizement panel, entertainment presentation system, kiosk system and so many applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1103-1109
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• 2014

The motion recognition system has been broadly studied in digital image and video processing fields. Recently, method using th depth image is used very useful. However, recognition accuracy of depth image based method will be loss caused by size and shape of object distorted for angle of the depth sensor. Therefore, distortion correction of depth sensor is positively necessary for distinguished performance of the recognition system. In this paper, we propose a pre-processing algorithm to improve the motion recognition system. Depth data from depth sensor converted to real world, performed the corrected angle, and then inverse converted to projective world. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2632-2649
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• 2012

Most approaches to human action recognition is limited due to the use of simple action datasets under controlled environments or focus on excessively localized features without sufficiently exploring the spatio-temporal information. This paper proposed a framework for recognizing realistic human actions. Specifically, a new action representation is proposed based on computing a rich set of descriptors from keypoint trajectories. To obtain efficient and compact representations for actions, we develop a feature fusion method to combine spatial-temporal local motion descriptors by the movement of the camera which is detected by the distribution of spatio-temporal interest points in the clips. A new topic model called Markov Semantic Model is proposed for semantic feature selection which relies on the different kinds of dependencies between words produced by "syntactic " and "semantic" constraints. The informative features are selected collaboratively based on the different types of dependencies between words produced by short range and long range constraints. Building on the nonlinear SVMs, we validate this proposed hierarchical framework on several realistic action datasets.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.21-28
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• 2019

Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.676-683
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• 2007

A non-invasive respiratory gated radiotherapy system like those based on external anatomic motion gives better comfortableness to patients than invasive system on treatment. However, higher correlation between the external and internal anatomic motion is required to increase the effectiveness of non-invasive respiratory gated radiotherapy. Both of invasive and non-invasive methods need to track the internal anatomy with the higher precision and rapid response. Especially, the non-invasive method has more difficulty to track the target position successively because of using only image processing. So we developed the system to track the motion for a non-invasive respiratory gated system to accurately find the dynamic position of internal structures such as the diaphragm and tumor. The respiratory organ motion tracking apparatus consists of an image capture board, a fluoroscopy system and a processing computer. After the image board grabs the motion of internal anatomy through the fluoroscopy system, the computer acquires the organ motion tracking data by image processing without any additional physical markers. The patients breathe freely without any forced breath control and coaching, when this experiment was performed. The developed pattern-recognition software could extract the target motion signal in real-time from the acquired fluoroscopic images. The range of mean deviations between the real and acquired target positions was measured for some sample structures in an anatomical model phantom. The mean and max deviation between the real and acquired positions were less than 1mm and 2mm respectively with the standardized movement using a moving stage and an anatomical model phantom. Under the real human body, the mean and maximum distance of the peak to trough was measured 23.5mm and 55.1mm respectively for 13 patients' diaphragm motion. The acquired respiration profile showed that human expiration period was longer than the inspiration period. The above results could be applied to respiratory-gated radiotherapy.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1263-1269
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• 2014

As rapid development of new hardware control interface technology, new concepts have been being proposed and emerged. In this paper, a new approach based on leap motion system is proposed. While we employ a position information from sensor, the hand gesture recognition is suggested with the pre-defined patterns. To do this, we design a recognition algorithm with hand gesture and finger patterns. We apply the proposed scheme to 3-dimensional avatar controling and editing software tool for making animation in the cyber space as a representative application. This proposed algorithm can be used to control computer systems in medical treatment, game, education and other various areas.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.384-386
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• 1998

The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction(HCI). Many methods hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network(NN), Hidden Markov Model(HMM) and so on. In our research, a HMMs is proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin-color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and thus, produces a trajectory. The spotting a feature database, the proposed approach use the mesh feature code for codebook of HMM. In our experiments, 1300 alphabetical and 1300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfying recognition rate for the images with different sizes, shapes and skew angles.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.1-8
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• 2010

Recently, the character image processing technology using portable device camera image at home and abroad are actively conducted, but Practical use are lower rate because of accuracy and time-consuming process problems. In this paper, we propose the license plate recognition method based on geometric information from portable device camera image. In the extracted license plate region we recognize characters using the chain code and the Thickness information through the cumulative projected edge after performing the pre-processing work considering the angle difference, the contrast enhancement and the low resolution from portable device camera image. The proposed algorithm is effective and accurate recognition by light and reducing the processing time. And, the results from the character recognition success rate was 95%. In the future, we will research about license plate recognition algorithm using long distance image or added motion blur image.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.343-352
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• 2012

In this paper, we implemented a touchless interface for DID(Digital Information Display) system using gesture recognition technique which includes both hand motion and hand shape recognition. Especially this touchless interface without extra attachments gives user both easier usage and spatial convenience. For hand motion recognition, two hand-motion's parameters such as a slope and a velocity were measured as a direction-based recognition way. And extraction of hand area image utilizing YCbCr color model and several image processing methods were adopted to recognize a hand shape recognition. These recognition methods are combined to generate various commands, such as, next-page, previous-page, screen-up, screen-down and mouse -click in oder to control DID system. Finally, experimental results showed the performance of 93% command recognition rate which is enough to confirm the possible application to commercial products.